Particle filter planar target tracking with a monocular camera for mobile robots. Issue 1 (2nd January 2017) - Chou, Yu-Cheng; Nakajima, Madoka
Abstract: This paper presents an effective and simple target tracking approach called PSIPT (Particle filter Single Image based Planar Target tracking). Compared with other works, the uniqueness of PSIPT includes: (1) only a single color camera provides the images to be processed; (2) the particle filter does not perform data fusion calculations; (3) the distance evaluation carried out in the particle filter does not need the camera's intrinsic and extrinsic parameters. Meanwhile, this paper also reveals that, under different target shapes and cameras, a high degree of negative linear dependence remains between: (1) a target's pixel height and vertical distance; (2) a target's vertical distance and PWHD (Pixel-Width-to-Horizontal Distance) ratio. According to the experimental results, PSIPT performs better than its Kalman filter variant in both the L-shape and S-shape tracking experiments. In addition, PSIPT has moderate performance in the target missing surveillance experiment. Moreover, a hybrid and enhanced version of PSIPT, which is equipped with an AdaBoost classifier in this study, leads to good surveillance performance in the target missing experiment.